Centralized Multisensor Unscented Joint Probabilistic Data Association Algorithm

被引：1

作者：

Guan, Xu-Jun ^{[1
]}

Rui, Guo-Sheng ^{[1
]}

Zhou, Xu ^{[1
]}

Xie, Xiao-ping ^{[2
]}

机构：

[1] Naval Aeronaut & Astronaut Univ, Elect & Informat Engn Dept, Yantai, Shandong, Peoples R China

[2] Navy Zhanjiang Base, Ordnance Maintenance Depot, Guangdong, Peoples R China

来源：

2009 INTERNATIONAL ASIA CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION, AND ROBOTICS, PROCEEDINGS | 2009年

关键词：

UKF; joint probabilistic data association; multitarget; multisensor; nonlinearity;

D O I：

10.1109/CAR.2009.90

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A centralized multisensor unscented joint probabilistic data association algorithm, CMSUJPDA, is proposed for the multisensor multitarget tracking problem of the nonlinear system in clutter. In the algorithm, UKF is used for the propagation of state distribution in the nonlinear system at first. Then the association of measurements to track is implemented according to the method of JPDA. Based on this, the CMSUJPDA algorithm is derived by use of the idea of sequential MSJPDA. Due to higher order of accuracy of UKF than EKF, the association probabilities and state estimates in our algorithm are not affected by the linearization error. Hence compared with MSJPDA/EKF, the accuracy and robustness of CMSUJPDA are more favorable. Finally simulation results show the superiority of the proposed algorithm.

引用

页码：301 / +

页数：2

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